[R] Recursive partitioning algorithms in R vs. alia

[Tobias Verbeke]

Wensui Liu wrote:

> in terms of the richness of features and ability to handle large
> data(which is normal in bank), SAS EM should be on top of others.

Should be ? That is not at all my experience.
SAS EM is very much lagging behind current
research. You will find variants of random forests
in R that will not be in SAS for the next 8 years,
to give just one example.

> however, it is not cheap.
> in terms of algorithm, split procedure in sas em can do
> chaid/cart/c4.5, if i remember correctly.

These are techniques of the 80s and 90s
(which proves my point). CART is in rpart and
an implementation of C4.5 can be accessed
through RWeka. For the oldest one (CHAID, 1980),
there might be an implementation soon:

http://r-forge.r-project.org/projects/chaid/

but again there have been quite some improvements
in the last decade as well:

http://cran.r-project.org/web/views/MachineLearning.html

HTH,
Tobias

> On Fri, Jun 19, 2009 at 2:35 PM, Carlos J. Gil
> Bellosta<cgb at datanalytics.com> wrote:
>> Dear R-helpers,
>>
>> I had a conversation with a guy working in a "business intelligence"
>> department at a major Spanish bank. They rely on recursive partitioning
>> methods to rank customers according to certain criteria.
>>
>> They use both SAS EM and Salford Systems' CART. I have used package R
>> part in the past, but I could not provide any kind of feature comparison
>> or the like as I have no access to any installation of the first two
>> proprietary products.
>>
>> Has anybody experience with them? Is there any public benchmark
>> available? Is there any very good --although solely technical-- reason
>> to pay hefty software licences? How would the algorithms implemented in
>> rpart compare to those in SAS and/or CART?
>>
>> Best regards,
>>
>> Carlos J. Gil Bellosta
>> http://www.datanalytics.com
>>
>> ______________________________________________
>> R-help at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
> 
> 
>